The authors present in [11] a low-cost health monitoring system that provides
continuous remote monitoring of the ECG and automatic analysis and notification. The
system consists of energy-efficient sensor nodes and a fog layer that take full advantage
of IoT. The sensor nodes collect and wirelessly transmit ECG, respiration rate, and
body temperature to a smart gateway which can be accessed by appropriate care-givers.
In addition, the system can represent the collected data in useful ways, perform
automatic decision making and provide many advanced services such as real-time
notifications for immediate attention.
All the previous proposed solutions require different technology skills to modify or
to scale out an existing system in a hospital context. The devices list is predefined at the
conception level with fixed parameters of configuration. Added to that, the frequency
of collecting and saving data are defined by the developers at the level of implementation without the possibility of modification after the deployment in a real case. As a
result of this static configuration, a device collect data with the same parameters defined
from the first step of development and it cannot be reused for personalized cases.
However, patient data are different from other collected data in IoT environments as
it depends on the no stable situation of the patient health. For example, the frequency of
the collected respiration data with a sensor depends on the patient illness. In some
cases, an interval of 1 h is sufficient but in other cases 1 min is needed. If the storage
operation of data is unique, an important unnecessary information will take place in the
memory and demand useless process. In this paper, we propose a health-care system
that makes it easy to personalize the vital signs monitoring of a particular patient
depending on his health condition.
3 The Proposed Solution
Our proposed solution supports a patient-driven process by giving the possibility to
adjust the parameters of vital signs monitoring to a specific health condition or treatment. The following paragraphs describe the solution architecture and the supported
communication model.
3.1 Publish-Subscribe Communication Model
Our solution uses the publish/subscribe pattern for the data exchange between the
different architecture layers. Publish-subscribe messaging systems support data-centric
communication and have been widely used in IoT systems. With the publish-subscribe
pattern, the exchange of messages between clients is ensured using a broker that
manages topics and sub-topics. A publisher on a given topic can send messages to other
clients acting as subscribers to the topic without the need to know about the existence
of the receiving clients [5].
To organize the topics and sub-topics in both gateway and server brokers, we define
four categories of data:
• Sensed data: The collection of time-series data sensed by the medical devices.
20
I. Ben Ida et al.
continuous remote monitoring of the ECG and automatic analysis and notification. The
system consists of energy-efficient sensor nodes and a fog layer that take full advantage
of IoT. The sensor nodes collect and wirelessly transmit ECG, respiration rate, and
body temperature to a smart gateway which can be accessed by appropriate care-givers.
In addition, the system can represent the collected data in useful ways, perform
automatic decision making and provide many advanced services such as real-time
notifications for immediate attention.
All the previous proposed solutions require different technology skills to modify or
to scale out an existing system in a hospital context. The devices list is predefined at the
conception level with fixed parameters of configuration. Added to that, the frequency
of collecting and saving data are defined by the developers at the level of implementation without the possibility of modification after the deployment in a real case. As a
result of this static configuration, a device collect data with the same parameters defined
from the first step of development and it cannot be reused for personalized cases.
However, patient data are different from other collected data in IoT environments as
it depends on the no stable situation of the patient health. For example, the frequency of
the collected respiration data with a sensor depends on the patient illness. In some
cases, an interval of 1 h is sufficient but in other cases 1 min is needed. If the storage
operation of data is unique, an important unnecessary information will take place in the
memory and demand useless process. In this paper, we propose a health-care system
that makes it easy to personalize the vital signs monitoring of a particular patient
depending on his health condition.
3 The Proposed Solution
Our proposed solution supports a patient-driven process by giving the possibility to
adjust the parameters of vital signs monitoring to a specific health condition or treatment. The following paragraphs describe the solution architecture and the supported
communication model.
3.1 Publish-Subscribe Communication Model
Our solution uses the publish/subscribe pattern for the data exchange between the
different architecture layers. Publish-subscribe messaging systems support data-centric
communication and have been widely used in IoT systems. With the publish-subscribe
pattern, the exchange of messages between clients is ensured using a broker that
manages topics and sub-topics. A publisher on a given topic can send messages to other
clients acting as subscribers to the topic without the need to know about the existence
of the receiving clients [5].
To organize the topics and sub-topics in both gateway and server brokers, we define
four categories of data:
• Sensed data: The collection of time-series data sensed by the medical devices.
20
I. Ben Ida et al.